Comparative composition of bacteria in the human intestinal microflora during remission and active ulcerative colitis

Ulcerative colitis is a severe, relapsing and remitting disease of the human large intestine characterised by inflammation of the mucosa and submucosa. The main site of disease is the sigmoid/rectal region of the large bowel but the aetiology remains unknown. There is considerable evidence to indicate that the components of the resident colonic microflora can play an important role in initiation of the disease. The present study was aimed at characterising the faecal microflora of ulcerative colitis patients in remission and active phases to determine profile differences. Faecal samples were obtained from 12 patients, 6 with active colitis and 6 in remission. The samples were analysed for populations of lactobacilli, bifidobacteria, clostridia, bacteroides, sulphate-reducing bacteria (SRB) and total bacteria using culture independent fluorescence in situ hybridisation (FISH). Lactobacillus-specific denaturing gradient gel electrophoresis (DGGE) was then performed to compare the species present. Numbers of lactobacilli were significantly lower (p<0.05) during the active phase of the disease but the other populations tested did not differ. DGGE analysis revealed that Lactobacillus salivarus, Lactobacillus manihotivorans and Pediococcus acidilactici were present in remission, but not during active inflammation. These results imply that a reduction in intestinal Lactobacillus species may be important in the initiation of ulcerative colitis.

Magnetic resonance imaging of a randomized controlled trial investigating predictors of recovery following psychological treatment in adolescents with moderate to severe unipolar depression: study protocol for Magnetic Resonance - Improving Mood with Psychoanalytic and Cognitive Therapies (MR-IMPACT)

Background Major depressive disorders (MDD) are a debilitating and pervasive group of mental illnesses afflicting many millions of people resulting in the loss of 110 million working days and more than 2,500 suicides per annum. Adolescent MDD patients attending NHS clinics show high rates of recurrence into adult life. A meta-analysis of recent research shows that psychological treatments are not as efficacious as previously thought. Modest treatment outcomes of approximately 65% of cases responding suggest that aetiological and clinical heterogeneity may hamper the better use of existing therapies and discovery of more effective treatments. Information with respect to optimal treatment choice for individuals is lacking, with no validated biomarkers to aid therapeutic decision-making. Methods/Design Magnetic resonance-Improving Mood with Psychoanalytic and Cognitive Therapies, the MR-IMPACT study, plans to identify brain regions implicated in the pathophysiology of depressions and examine whether there are specific behavioural or neural markers predicting remission and/or subsequent relapse in a subsample of depressed adolescents recruited to the IMPACT randomised controlled trial (Registration # ISRCTN83033550). Discussion MR-IMPACT is an investigative biomarker component of the IMPACT pragmatic effectiveness trial. The aim of this investigation is to identify neural markers and regional indicators of the pathophysiology of and treatment response for MDD in adolescents. We anticipate that these data may enable more targeted treatment delivery by identifying those patients who may be optimal candidates for therapeutic response.

Radically open-dialectical behavior therapy for adult anorexia nervosa: feasibility and outcomes from an inpatient program

Background Anorexia Nervosa (AN) is a highly life-threatening disorder that is extremely difficult to treat. There is evidence that family-based therapies are effective for adolescent AN, but no treatment has been proven to be clearly effective for adult AN. The methodological challenges associated with studying the disorder have resulted in recommendations that new treatments undergo preliminary testing prior to being evaluated in a randomized clinical trial. The aim of this study was to provide preliminary evidence on the effectiveness of a treatment program based on a novel adaptation of Dialectical Behavior Therapy (DBT) for adult Anorexia Nervosa (Radically Open-DBT; RO-DBT) that conceptualizes AN as a disorder of overcontrol. Methods Forty-seven individuals diagnosed with Anorexia Nervosa-restrictive type (AN-R; mean admission body mass index = 14.43) received the adapted DBT inpatient program (mean length of treatment = 21.7 weeks). Results Seventy-two percent completed the treatment program demonstrating substantial increases in body mass index (BMI; mean change in BMI = 3.57) corresponding to a large effect size (d = 1.91). Thirty-five percent of treatment completers were in full remission, and an additional 55% were in partial remission resulting in an overall response rate of 90%. These same individuals demonstrated significant and large improvements in eating-disorder related psychopathology symptoms (d = 1.17), eating disorder-related quality of life (d = 1.03), and reductions in psychological distress (d = 1.34). Conclusions RO-DBT was associated with significant improvements in weight gain, reductions in eating disorder symptoms, decreases in eating-disorder related psychopathology and increases in eating disorder-related quality of life in a severely underweight sample. These findings provide preliminary support for RO-DBT in treating AN-R suggesting the importance of further evaluation examining long-term outcomes using randomized controlled trial methodology.

Effective elements of cognitive behaviour therapy for psychosis: results of a novel type of subgroup analysis based on principal stratification

Background. Meta-analyses show that cognitive behaviour therapy for psychosis (CBT-P) improves distressing positive symptoms. However, it is a complex intervention involving a range of techniques. No previous study has assessed the delivery of the different elements of treatment and their effect on outcome. Our aim was to assess the differential effect of type of treatment delivered on the effectiveness of CBT-P, using novel statistical methodology. Method. The Psychological Prevention of Relapse in Psychosis (PRP) trial was a multi-centre randomized controlled trial (RCT) that compared CBT-P with treatment as usual (TAU). Therapy was manualized, and detailed evaluations of therapy delivery and client engagement were made. Follow-up assessments were made at 12 and 24 months. In a planned analysis, we applied principal stratification (involving structural equation modelling with finite mixtures) to estimate intention-to-treat (ITT) effects for subgroups of participants, defined by qualitative and quantitative differences in receipt of therapy, while maintaining the constraints of randomization. Results. Consistent delivery of full therapy, including specific cognitive and behavioural techniques, was associated with clinically and statistically significant increases in months in remission, and decreases in psychotic and affective symptoms. Delivery of partial therapy involving engagement and assessment was not effective. Conclusions. Our analyses suggest that CBT-P is of significant benefit on multiple outcomes to patients able to engage in the full range of therapy procedures. The novel statistical methods illustrated in this report have general application to the evaluation of heterogeneity in the effects of treatment.

Multiscale evolving complex network model of functional connectivity in neuronal cultures

Cultures of cortical neurons grown on multielectrode arrays exhibit spontaneous, robust and recurrent patterns of highly synchronous activity called bursts. These bursts play a crucial role in the development and topological selforganization of neuronal networks. Thus, understanding the evolution of synchrony within these bursts could give insight into network growth and the functional processes involved in learning and memory. Functional connectivity networks can be constructed by observing patterns of synchrony that evolve during bursts. To capture this evolution, a modelling approach is adopted using a framework of emergent evolving complex networks and, through taking advantage of the multiple time scales of the system, aims to show the importance of sequential and ordered synchronization in network function.

The relative order and inverses of recurrent networks

Differential geometry is used to investigate the structure of neural-network-based control systems. The key aspect is relative order—an invariant property of dynamic systems. Finite relative order allows the specification of a minimal architecture for a recurrent network. Any system with finite relative order has a left inverse. It is shown that a recurrent network with finite relative order has a local inverse that is also a recurrent network with the same weights. The results have implications for the use of recurrent networks in the inverse-model-based control of nonlinear systems.

Dynamic recurrent neural network for system identification and control

A dynamic recurrent neural network (DRNN) that can be viewed as a generalisation of the Hopfield neural network is proposed to identify and control a class of control affine systems. In this approach, the identified network is used in the context of the differential geometric control to synthesise a state feedback that cancels the nonlinear terms of the plant yielding a linear plant which can then be controlled using a standard PID controller.

Coupling between gamma-band power and cerebral blood volume during recurrent acute neocortical seizures

Characterization of neural and hemodynamic biomarkers of epileptic activity that can be measured using noninvasive techniques is fundamental to the accurate identification of the epileptogenic zone (EZ) in the clinical setting. Recently, oscillations at gamma-band frequencies and above (N30 Hz) have been suggested to provide valuable localizing information of the EZ and track cortical activation associated with epileptogenic processes. Although a tight coupling between gamma-band activity and hemodynamic-based signals has been consistently demonstrated in non-pathological conditions, very little is known about whether such a relationship is maintained in epilepsy and the laminar etiology of these signals. Confirmation of this relationship may elucidate the underpinnings of perfusion-based signals in epilepsy and the potential value of localizing the EZ using hemodynamic correlates of pathological rhythms. Here, we use concurrent multi-depth electrophysiology and 2- dimensional optical imaging spectroscopy to examine the coupling between multi-band neural activity and cerebral blood volume (CBV) during recurrent acute focal neocortical seizures in the urethane-anesthetized rat. We show a powerful correlation between gamma-band power (25–90 Hz) and CBV across cortical laminae, in particular layer 5, and a close association between gamma measures and multi-unit activity (MUA). Our findings provide insights into the laminar electrophysiological basis of perfusion-based imaging signals in the epileptic state and may have implications for further research using non-invasive multi-modal techniques to localize epileptogenic tissue

The psychological, neurochemical and functional neuroanatomical mediators of the effects of positive and negative mood on executive functions

In this review we evaluate the cognitive and neural effects of positive and negative mood on executive function. Mild manipulations of negative mood appear to have little effect on cognitive control processes, whereas positive mood impairs aspects of updating, planning and switching. These cognitive effects may be linked to neurochemistry: with positive mood effects mediated by dopamine while negative mood effects may be mediated by serotonin levels. Current evidence on the effects of mood on regional brain activity during executive functions, indicates that the prefrontal cortex is a recurrent site of integration between mood and cognition. We conclude that there is a disparity between the importance of this topic and awareness of how mood affects, executive functions in the brain. Most behavioural and neuroimaging studies of executive function in normal samples do not explore the potential role of variations in mood, yet the evidence we outline indicates that even mild fluctuations in mood can have a significant influence on neural activation and cognition. (c) 2006 Elsevier Ltd. All rights reserved.

Maternal depression and psychiatric outcomes in adolescent offspring: a13-year longitudinal study

Background: Maternal postnatal depression (PND) has been associated with adverse outcomes in young children, but an association with longer-term psychiatric disorder has not been demonstrated. We present the preliminary findings of a 13-year longitudinal study. Methods: In the course of a prospective longitudinal study, we examined DSM-IV Axis I disorders in 13-year-old adolescents who had (n=53) or had not (n=41) been exposed to maternal PND. We also detailed the occurrence of depression in mothers throughout the 13-year follow-up period. Results: Maternal PND was associated with higher rates of affective disorders in adolescent offspring. However, mothers who developed PND were also substantially more likely than those who did not to experience depression subsequently, a fact that contributed to the development of depressive disorder in offspring. Maternal PND was associated with increased risk for depression in adolescent offspring only if there had also been later episodes of maternal depression. In contrast, anxiety disorders in offspring were elevated in the maternal PND group regardless of the occurrence of subsequent maternal depression. Limitations: Due to the modest sample size and consequently limited power, findings must be regarded as preliminary. Conclusions: The particular association between early maternal depression and anxiety disorders in offspring was consistent with theories that emphasise the primacy of early environmental exposures. This position was not supported with respect to offspring depressive disorder, where overall duration of maternal depression was a significant factor. PND was associated with recurrent episodes of depression in the majority of cases, underlining the need for monitoring of this population beyond the postnatal period. (c) 2006 Elsevier B.V. All rights reserved.

Controlled trial of the short- and long-term effect of psychological treatment of post-partum depression - 1. Impact on maternal mood!

Background: Psychological interventions for postnatal depression can be beneficial in the short term but their longer-term impact is unknown, Aims To evaluate the long-term effect on maternal mood of three psychological treatments in relation to routine primary care. Method: Women with post-partum depression (n=193)were assigned randomly to one of four conditions: routine primary care, non-directive counselling, cognitive-behavioural therapy or psychodynamic therapy. They were assessed immediately after the treatment phase (at 4.5 months) and at 18 and 60 months post-partum. Results: Compared with the control, ail three treatments had a significant impact at 4.5 months on maternal mood (Edinburgh Postnatal Depression Scale, EPDS). Only psychodynamic therapy produced a rate of reduction in depression (Structured Clinical interview for DSM III-R) significantly superior to that of the control. The benefit of treatment was no longer apparent by 9 months postpartum, treatment did not reduce subsequent episodes of post-partum depression. Conclusions: Psychological intervention for post-partum depression improves maternal mood (EPDS) in the short term. However, this benefit is not superior to spontaneous remission in the long term.

Inverse model control using recurrent networks

This paper illustrates how internal model control of nonlinear processes can be achieved by recurrent neural networks, e.g. fully connected Hopfield networks. It is shown that using results developed by Kambhampati et al. (1995), that once a recurrent network model of a nonlinear system has been produced, a controller can be produced which consists of the network comprising the inverse of the model and a filter. Thus, the network providing control for the nonlinear system does not require any training after it has been trained to model the nonlinear system. Stability and other issues of importance for nonlinear control systems are also discussed.

Input/output linearization using dynamic recurrent neural networks

This paper brings together two areas of research that have received considerable attention during the last years, namely feedback linearization and neural networks. A proposition that guarantees the Input/Output (I/O) linearization of nonlinear control affine systems with Dynamic Recurrent Neural Networks (DRNNs) is formulated and proved. The proposition and the linearization procedure are illustrated with the simulation of a single link manipulator.

Stable receding horizon control based on recurrent networks

The last decade has seen the re-emergence of artificial neural networks as an alternative to traditional modelling techniques for the control of nonlinear systems. Numerous control schemes have been proposed and have been shown to work in simulations. However, very few analyses have been made of the working of these networks. The authors show that a receding horizon control strategy based on a class of recurrent networks can stabilise nonlinear systems.